Next Article in Journal
Downscaling Surface Water Inundation from Coarse Data to Fine-Scale Resolution: Methodology and Accuracy Assessment
Next Article in Special Issue
Correction of Interferometric and Vegetation Biases in the SRTMGL1 Spaceborne DEM with Hydrological Conditioning towards Improved Hydrodynamics Modeling in the Amazon Basin
Previous Article in Journal
Precise Positioning of BDS, BDS/GPS: Implications for Tsunami Early Warning in South China Sea
Previous Article in Special Issue
On the Use of Global Flood Forecasts and Satellite-Derived Inundation Maps for Flood Monitoring in Data-Sparse Regions
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2015, 7(12), 15969-15988; doi:10.3390/rs71215805

Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices

1
International Centre for Water Hazard and Risk Management (ICHARM) under the auspices of UNESCO, 1-6 Minamihara, Tsukuba 305-8516, Japan
2
Flood Forecasting & Warning Center, Bangladesh Water Development Board, Dhaka 1000, Bangladesh
*
Author to whom correspondence should be addressed.
Academic Editors: Guy J-P. Schumann, Magaly Koch and Prasad S. Thenkabail
Received: 22 June 2015 / Revised: 16 November 2015 / Accepted: 17 November 2015 / Published: 30 November 2015
(This article belongs to the Special Issue Remote Sensing in Flood Monitoring and Management)
View Full-Text   |   Download PDF [6833 KB, uploaded 30 November 2015]   |  

Abstract

Flood mapping, particularly hazard and risk mapping, is an imperative process and a fundamental part of emergency response and risk management. This paper aims to produce a flood risk proxy map of damaged rice fields over the whole of Bangladesh, where monsoon river floods are dominant and frequent, affecting over 80% of the total population. This proxy risk map was developed to meet the request of the government on a national level. This study represents a rapid, straightforward methodology for estimating rice-crop damage in flood areas of Bangladesh during the large flood from July to September 2007, despite the lack of primary data. We improved a water detection algorithm to achieve a better discrimination capacity to discern flood areas by using a modified land surface water index (MLSWI). Then, rice fields were estimated utilizing a hybrid rice field map from land-cover classification and MODIS-derived indices, such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results showed that the developed method is capable of providing instant, comprehensive, nationwide mapping of flood risks, such as rice field damage. The detected flood areas and damaged rice fields during the 2007 flood were verified by comparing them with the Advanced Land Observing Satellite (ALOS) AVNIR-2 images (a 10 m spatial resolution) and in situ field survey data with moderate agreement (K = 0.57). View Full-Text
Keywords: flood mapping; MLSWI; EVI; rice crop; flood risk map; MODIS flood mapping; MLSWI; EVI; rice crop; flood risk map; MODIS
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Kwak, Y.; Arifuzzanman, B.; Iwami, Y. Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices. Remote Sens. 2015, 7, 15969-15988.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top